Optimized Method based on Lattice Sequences for Multidimensional Integrals in Neural Networks

In this work we investigate advanced stochastic methods for solving a specific multidimensional problem related to neural networks. Monte Carlo and quasi-Monte Carlo techniques have been developed over many years in a range of different fields, but have only recently been applied to the problems in neural networks. As well as providing a consistent framework for statistical pattern recognition, the stochastic approach offers a number of practical advantages including a solution to the problem for higher dimensions. For the first time multidimensional integrals up to 100 dimensions related to this area will be discussed in our numerical study.

---

1. Track 1: Artificial Intelligence in Applications

---

2. Session: 14th International Workshop on Computational Optimization

---

3. Short Paper